Using MapReducer for Long Contexts in QAEvaluator

I am hitting the Open API token limit while using the QAEvaluator . I see that there is a MapReducer type of evaluator that deals with long contexts by breaking them into chunks and aggregating the results after. However I could not find specific examples of how to use it. Can you point me to an example? If there isn't an example, then can you please give me some pointers on how to perform the same evaluation as a QAEvaluator using the map-reduce technique? TIA! https://github.com/Arize-ai/phoenix/blob/e24d7212ace403f0e396de027a7cfb9bd4a14657/packages/phoenix-evals/src/phoenix/evals/evaluators.py#L270